13 citations · 25 across the 13 of their papers we have counts for
5 papers · 1 filter
Membership Inference Attack on Private Evolution
Daniil Filienko, Sikha Pentyala, Martine De Cock
Synthetic Data Generation (SDG) is an actively studied way to enable safe sharing of private data more broadly. Inference-only SDG methods, such as Private Evolution (PE), are part…
Portable Causal Fairness Across Synthetic Data Generator Families
Steven Golob, Sikha Pentyala, Martine De Cock
When a statistical agency or regulator releases synthetic data in place of sensitive records, it chooses the generator that produces the table, and can shape that generator so unfa…
SoK: Reconstruction Attacks on Synthetic Tabular Data (Insights from Winning the NIST CRC)
Steven Golob, Sikha Pentyala, Martine De Cock
Synthetic data is increasingly promoted as a privacy-preserving substitute for releasing sensitive tabular records, yet its central adversarial threat (reconstruction, the recovery…
Federated Generation of Synthetic RNA-seq Data
Daniil Filienko, Martine De Cock, Sikha Pentyala
Access to genomic data is highly regulated due to its sensitive nature. While safeguards are essential, cumbersome data access processes pose a significant barrier to the developme…
FHAIM: Fully Homomorphic AIM For Private Synthetic Data Generation
Mayank Kumar, Qian Lou, Paulo Barreto +2
Data is the lifeblood of AI, yet much of the most valuable data remains locked in silos due to privacy and regulations. As a result, AI remains heavily underutilized in many of the…